Hello World

Author: OA Lab, NWFSC Title: Respirometry Trails for Summer Krill 2019 Date: November 2020

1.) Setting Working Directory

#*********************************
## 1.) Setting Working Directory
#*********************************

#set working directory to the correct folder
setwd("/Users/katherinerovinski/GIT/NWFSC.MUK_KRL2019respirometry")

2.) Creating the Dataframe

#*********************************
## 2.) Creating the intial Dataframe, dRESP
#*********************************

## Method 1 - 1 file for the four trials
#get all the files in the defined working directory that are in csv format
dRESP <- read.csv(file = "KRILL_Resp_alltrials.csv", stringsAsFactors = FALSE)
dim(dRESP)
## [1] 3756   52
write.csv(dRESP, file = "2020.11.06_presenseSENSORONLY.alltrials.data.csv", row.names = FALSE)
#|- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |


# dRESPanimal represents just the animal, vial, MOATs, etc.  
dRESPanimal <- read.csv(file = "RespirometryTrials_all.Animal.Info.csv") 
dim(dRESPanimal)
## [1] 76 10
write.csv(dRESPanimal, file = "2020.11.06_krillanimaldata.csv", row.names = FALSE)
#|- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |


#dRESPmsr represents the measurements made by the presense optical device for Dissolved Oxygen 
dRESPmsr <- merge(dRESP, dRESPanimal, by="SensorName")

write.csv(dRESPmsr, file = "2020.11.06_respirometrymeasurements.csv", row.names = FALSE)
#|- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |


# dRESP$MOATS <- factor(dRESP$MOATS)
# Checking the names of the different levels
# levels(dRESP$MOATS)


dRESPmsr <- dRESPmsr %>% filter(!MOATS %in% c("3", "4", "5", "11")) %>%
  filter(Treatment %in% c("CUR", "CHG", "TMP")) 

3.) Creating dateTime objects

#*********************************
## 3.) Creating dateTime objects  
#*********************************

dRESPmsr$dateTime <- ""
dRESPmsr$dateTime <- as.POSIXct(paste(dRESPmsr$Date,
                                      dRESPmsr$Time), "%d-%B-%y %H:%M:%S", tz="UTC")

# QA check
dim(dRESPmsr)
## [1] 2419   62
dRESPmsr$Time <- as.POSIXct(dRESPmsr$dateTime, format="%H:%M:%S")

4.) Cleaning up observations

#*********************************
## 4.) Cleaning up observations  
#********************************

#Removing items with faulty sensor names
dRESPmsr <- subset(dRESPmsr, SensorName != "")

dRESPmsr$SensorName <- str_trim(dRESPmsr$SensorName, side = c("both"))
dRESPmsr$SensorName <- factor(dRESPmsr$SensorName)
dim(dRESPmsr)
## [1] 2419   62
dRESPmsr <- subset(dRESPmsr, Value != "---")

# Confirming proper number of krill 
# 76, 4x19 propoer number of animals under observation 
unique(dRESPmsr$SensorName)
##  [1] KrilLR11 KrilLR13 KrilLR14 KrilLR15 KrilLR16 KrilLR17 KrilLR18 KrILR110
##  [9] KriLR111 KriLR112 KriLR113 KriLR114 KriLR115 KriLR116 KriLR117 KriLR118
## [17] KriLR119 KriLR220 KriLR223 KriLR226 KriLR227 KriLR229 KriLR232 KriLR233
## [25] KriLR234 KriLR235 KRLr3_39 KRLr3_40 KRLr3_41 KRLr3_42 KRLr3_44 KRLr3_45
## [33] KRLr3_46 KRLr3_47 KRLr3_48 KRLr3_49 KRLr3_50 KRLr3_51 KRLr3_53 KRLr3_54
## [41] KRLr3_55 KRLr3_56 KRLr3_57 KRLr4_58 KRLr4_62 KRLr4_67 KRLr4_70 KRLr4_75
## [49] KRLr4_76
## 49 Levels: KrilLR11 KrilLR13 KrilLR14 KrilLR15 KrilLR16 KrilLR17 ... KRLr4_76
UniqueSensorNames <- levels(dRESPmsr$SensorName)
write.table(UniqueSensorNames, file = "2020.11.06DRESPmsr_UniqueSensorNames.csv")
kable(UniqueSensorNames)
x
KrilLR11
KrilLR13
KrilLR14
KrilLR15
KrilLR16
KrilLR17
KrilLR18
KrILR110
KriLR111
KriLR112
KriLR113
KriLR114
KriLR115
KriLR116
KriLR117
KriLR118
KriLR119
KriLR220
KriLR223
KriLR226
KriLR227
KriLR229
KriLR232
KriLR233
KriLR234
KriLR235
KRLr3_39
KRLr3_40
KRLr3_41
KRLr3_42
KRLr3_44
KRLr3_45
KRLr3_46
KRLr3_47
KRLr3_48
KRLr3_49
KRLr3_50
KRLr3_51
KRLr3_53
KRLr3_54
KRLr3_55
KRLr3_56
KRLr3_57
KRLr4_58
KRLr4_62
KRLr4_67
KRLr4_70
KRLr4_75
KRLr4_76

#5.) Creating Trial ID & Krill ID

#*********************************
## 5.) Creating a Krill ID with Trial in name    
#*********************************

## First Trial began at 2019-10-28 14:25:01
## First Trial ended at 2019-10-28 16:37:29

## Second Trial began at 2019-10-28 18:55:21
## Second Trial ended at 2019-10-28 21:16:45

## Third Trial began at 2019-10-29 14:06:21
## Third Trial ended at 2019-10-29 16:18:36

## Fourth Trial began at 2019-10-29 17:20:21
## Fourth Trial ended at 2019-10-29 19:32:01


dRESPmsr$TrialID <- ""
dRESPmsr <- dRESPmsr %>% mutate(TrialID=case_when(
  
## First Trial began at 2019-10-28 14:25:01
## First Trial ended at 2019-10-28 16:37:29
  
  ((Time >= as.POSIXct("2019-10-28 14:25:00", tz = "UTC")) 
   & (Time < as.POSIXct("2019-10-28 16:37:30", tz = "UTC"))) ~ "Trial01",

  
## Second Trial began at 2019-10-28 18:55:21
## Second Trial ended at 2019-10-28 21:16:45  
  
  ((Time >= as.POSIXct("2019-10-28 18:55:20", tz = "UTC")) 
   & (Time <= as.POSIXct("2019-10-28 21:16:50", tz = "UTC"))) ~ "Trial02",


## Third Trial began at 2019-10-29 14:06:21
## Third Trial ended at 2019-10-29 16:18:36


  ((Time >= as.POSIXct("2019-10-29 14:06:18", tz = "UTC")) 
   & (Time <= as.POSIXct("2019-10-29 16:18:40", tz = "UTC"))) ~ "Trial03",

## Fourth Trial began at 2019-10-29 17:20:21
## Fourth Trial ended at 2019-10-29 19:32:01

  
  ((Time >= as.POSIXct("2019-10-29 17:20:18", tz = "UTC")) 
   & (Time <= as.POSIXct("2019-10-29 19:40:01", tz = "UTC"))) ~ "Trial04",

  TRUE ~"other"
)) 

#|- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |

## new value 
## dRESPmsr$KrillID

dRESPmsr$KrillID <- ""

dRESPmsr$KrillID <- paste(dRESPmsr$TrialID, "_", dRESPmsr$SensorName, sep="")
#View(dRESPmsr)

#|- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |

6.) DO Corrections

#*********************************
## 6.) DO trial 3 correction applied to all rounds   
#*********************************

# New values to correct the DO values for the temperature in Trial 3 in the dataframe dRESPmsr

dRESPmsr$percentDOassumpt <- ""
dRESPmsr$assumedSatDOmg <- ""
dRESPmsr$percentDO <- ""
dRESPmsr$obseveredSatDOmg <- ""
dRESPmsr$actualDOmg <- ""

dRESPmsr$percentDOassumpt <- as.numeric(dRESPmsr$percentDOassumpt)
dRESPmsr$assumedSatDOmg <- as.numeric(dRESPmsr$assumedSatDOmg)
dRESPmsr$percentDO <- as.numeric(dRESPmsr$percentDO)
dRESPmsr$obseveredSatDOmg <- as.numeric(dRESPmsr$obseveredSatDOmg)
dRESPmsr$actualDOmg <- as.numeric(dRESPmsr$actualDOmg)
#|- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |

#Correct Temperature
dRESPmsr$CorTemp <- 11

#Salinity Constant
dRESPmsr$SalinityConstant <- 30.3
#|- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |

# Numeric Corrections to DO value
dRESPmsr$Value <- as.numeric(dRESPmsr$Value)

dRESPmsr$assumedSatDOmg <- oxySol(dRESPmsr$CorTemp, 
                                  dRESPmsr$SalinityConstant)

dRESPmsr$percentDOassumpt <- dRESPmsr$Value / dRESPmsr$assumedSatDOmg

dRESPmsr$obseveredSatDOmg <- oxySol(dRESPmsr$CorTemp, dRESPmsr$SalinityConstant)

dRESPmsr$percentDO <- dRESPmsr$Value / dRESPmsr$assumedSatDOmg

dRESPmsr$actualDOmg <- dRESPmsr$percentDO * dRESPmsr$obseveredSatDOmg


#|- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |

6.a) DO table & DO correction Plot Check

#*********************************
## 6.a) DO table & DO correction Plot Check  
#*********************************

# write.table(dRESPmsr, file = "2020.11.06.dRESPmeasurements", sep=";", 
#             row.names = TRUE)
# 
# dRESPmsr <-subset(dRESPmsr, actualDOmg != "---")
# dRESPmsr$Time <- as.POSIXct(dRESPmsr$Time, format="%H:%M:%S")
ggplot(dRESPmsr, aes(x = Time, y = actualDOmg, colour = SensorName)) +
  geom_point(size = 1) +
  geom_smooth(method = "lm") +
  facet_wrap(~TrialID) +
  #scale_y_continuous(breaks=seq(250,950,by=50))   +
  theme_bw()
## `geom_smooth()` using formula 'y ~ x'

Filtering Broken MOATs

Plotting Animals on 80 Dissolved Oxygen

Trial1percentDO <- filter(dRESPmsr, TrialID == "Trial01")


ggplot(Trial1percentDO, aes(x = Time, y = percentDO, colour = SensorName)) +
  geom_point(size = 1) +
  geom_smooth(method = "lm") +
  #scale_y_continuous(breaks=seq(250,950,by=50))   +
  ggtitle("Trial01 Percent DO") +
  facet_wrap(~ Treatment) + 
  theme_bw()
## `geom_smooth()` using formula 'y ~ x'

Trial2percentDO <- filter(dRESPmsr, TrialID == "Trial02")


ggplot(Trial2percentDO, aes(x = Time, y = percentDO, colour = SensorName)) +
  geom_point(size = 1) +
  geom_smooth(method = "lm") +
  #scale_y_continuous(breaks=seq(250,950,by=50))   +
  ggtitle("Trial02 Percent DO") +
  facet_wrap(~ Treatment) + 
  theme_bw()
## `geom_smooth()` using formula 'y ~ x'

Trial3percentDO <- filter(dRESPmsr, TrialID == "Trial03")


ggplot(Trial3percentDO, aes(x = Time, y = percentDO, colour = SensorName)) +
  geom_point(size = 1) +
  geom_smooth(method = "lm") +
  #scale_y_continuous(breaks=seq(250,950,by=50))   +
  ggtitle("Trial03 Percent DO") +
  facet_wrap(~ Treatment) + 
  theme_bw()
## `geom_smooth()` using formula 'y ~ x'

Trial4percentDO <- filter(dRESPmsr, TrialID == "Trial04")


ggplot(Trial4percentDO, aes(x = Time, y = percentDO, colour = SensorName)) +
  geom_point(size = 1) +
  geom_smooth(method = "lm") +
  #scale_y_continuous(breaks=seq(250,950,by=50))   +
  ggtitle("Trial04 Percent DO") +
  facet_wrap(~ Treatment) + 
  theme_bw()
## `geom_smooth()` using formula 'y ~ x'

apply the blanks within trial don’t comare blanks across trials exhibit the blanks are showing a reduction in oxygen any time that there is “evidence” of oxygen production place to zero

background bacteria breathing our water investigation

7.) Analysis, Respirometry - Creating the Slope Function

#*********************************
## 7.) Analysis, Respirometry - Creating the Slope Function  
#*********************************  

vialVol <- 28.06 #ml

oxygen <- vialVol * dRESPmsr$actualDOmg   

dRESPmsr$oxygen <- oxygen

#nmol/vial; conversion for L to ml and umol to nmol cancels


#slope funcion of 2 vectors
slope <- function(y,x){
  return(lm(y~x, na.action = na.omit)$coefficients[2])
}
  

dRESPmsr$delta_t <- as.numeric(dRESPmsr$delta_t)

cSlopes <- by(dRESPmsr, dRESPmsr$KrillID, function(x){ slope(x$oxygen, x$delta_t)})


#creating a data frame instead of a list 
ds <- as.data.frame(sapply(cSlopes, I))
#having row names be a variable in a column to be able to pull it out for later merging 
ds$TrialID<- row.names(ds)

8.) Creating the ds dataframe

#*********************************
## 8.) Creating the ds dataframe
#*********************************

#creating a data frame instead of a list 
ds <- as.data.frame(sapply(cSlopes, I))
#having row names be a variable in a column to be able to pull it out for later merging 
ds$TrialID<- row.names(ds)

dim(ds)
## [1] 49  2
#add column to dslopes thats KrillID
#View(dref)
ds$KrillID <- row.names(ds)
#View(dslopes)
dtotal <- merge(dRESPmsr, ds, by = "KrillID")
#View(dtotal)

unique(dtotal$KrillID)
##  [1] "Trial01_KrilLR11" "Trial01_KrilLR13" "Trial01_KrilLR14" "Trial01_KrilLR15"
##  [5] "Trial01_KrilLR16" "Trial01_KrilLR17" "Trial01_KrilLR18" "Trial01_KrILR110"
##  [9] "Trial01_KriLR111" "Trial01_KriLR112" "Trial01_KriLR113" "Trial01_KriLR114"
## [13] "Trial01_KriLR115" "Trial01_KriLR116" "Trial01_KriLR117" "Trial01_KriLR118"
## [17] "Trial01_KriLR119" "Trial02_KriLR220" "Trial02_KriLR223" "Trial02_KriLR226"
## [21] "Trial02_KriLR227" "Trial02_KriLR229" "Trial02_KriLR232" "Trial02_KriLR233"
## [25] "Trial02_KriLR234" "Trial02_KriLR235" "Trial03_KRLr3_39" "Trial03_KRLr3_40"
## [29] "Trial03_KRLr3_41" "Trial03_KRLr3_42" "Trial03_KRLr3_44" "Trial03_KRLr3_45"
## [33] "Trial03_KRLr3_46" "Trial03_KRLr3_47" "Trial03_KRLr3_48" "Trial03_KRLr3_49"
## [37] "Trial03_KRLr3_50" "Trial03_KRLr3_51" "Trial03_KRLr3_53" "Trial03_KRLr3_54"
## [41] "Trial03_KRLr3_55" "Trial03_KRLr3_56" "Trial03_KRLr3_57" "Trial04_KRLr4_58"
## [45] "Trial04_KRLr4_62" "Trial04_KRLr4_67" "Trial04_KRLr4_70" "Trial04_KRLr4_75"
## [49] "Trial04_KRLr4_76"
UniqueKrillIDs <- levels(dtotal$KrillID)
write.table(UniqueKrillIDs, file = "2020.11.06dtotal_UniqueKrillIDs.csv")
#kable(UniqueSensorNames)

9.) Creating Slope Functions & Linear Models

#*********************************
## 9.) Creating the ds dataframe
#*********************************
# #get slopes and r^2 values from dtotal - just adjusted code from data analysis to fit into these df's
dtotal$KrillID <- factor(dtotal$KrillID)
nlevels(dtotal$KrillID)
## [1] 49
dtotal[is.na(dtotal$delta_t),]
unique(dtotal$KrillID)
##  [1] Trial01_KrilLR11 Trial01_KrilLR13 Trial01_KrilLR14 Trial01_KrilLR15
##  [5] Trial01_KrilLR16 Trial01_KrilLR17 Trial01_KrilLR18 Trial01_KrILR110
##  [9] Trial01_KriLR111 Trial01_KriLR112 Trial01_KriLR113 Trial01_KriLR114
## [13] Trial01_KriLR115 Trial01_KriLR116 Trial01_KriLR117 Trial01_KriLR118
## [17] Trial01_KriLR119 Trial02_KriLR220 Trial02_KriLR223 Trial02_KriLR226
## [21] Trial02_KriLR227 Trial02_KriLR229 Trial02_KriLR232 Trial02_KriLR233
## [25] Trial02_KriLR234 Trial02_KriLR235 Trial03_KRLr3_39 Trial03_KRLr3_40
## [29] Trial03_KRLr3_41 Trial03_KRLr3_42 Trial03_KRLr3_44 Trial03_KRLr3_45
## [33] Trial03_KRLr3_46 Trial03_KRLr3_47 Trial03_KRLr3_48 Trial03_KRLr3_49
## [37] Trial03_KRLr3_50 Trial03_KRLr3_51 Trial03_KRLr3_53 Trial03_KRLr3_54
## [41] Trial03_KRLr3_55 Trial03_KRLr3_56 Trial03_KRLr3_57 Trial04_KRLr4_58
## [45] Trial04_KRLr4_62 Trial04_KRLr4_67 Trial04_KRLr4_70 Trial04_KRLr4_75
## [49] Trial04_KRLr4_76
## 49 Levels: Trial01_KrilLR11 Trial01_KrilLR13 ... Trial04_KRLr4_76
#how best to run the lmlist over
# group and then run a function tidyverse
# group by krill ID and then run the function

levels(dtotal$KrillID)
##  [1] "Trial01_KrilLR11" "Trial01_KrilLR13" "Trial01_KrilLR14" "Trial01_KrilLR15"
##  [5] "Trial01_KrilLR16" "Trial01_KrilLR17" "Trial01_KrilLR18" "Trial01_KrILR110"
##  [9] "Trial01_KriLR111" "Trial01_KriLR112" "Trial01_KriLR113" "Trial01_KriLR114"
## [13] "Trial01_KriLR115" "Trial01_KriLR116" "Trial01_KriLR117" "Trial01_KriLR118"
## [17] "Trial01_KriLR119" "Trial02_KriLR220" "Trial02_KriLR223" "Trial02_KriLR226"
## [21] "Trial02_KriLR227" "Trial02_KriLR229" "Trial02_KriLR232" "Trial02_KriLR233"
## [25] "Trial02_KriLR234" "Trial02_KriLR235" "Trial03_KRLr3_39" "Trial03_KRLr3_40"
## [29] "Trial03_KRLr3_41" "Trial03_KRLr3_42" "Trial03_KRLr3_44" "Trial03_KRLr3_45"
## [33] "Trial03_KRLr3_46" "Trial03_KRLr3_47" "Trial03_KRLr3_48" "Trial03_KRLr3_49"
## [37] "Trial03_KRLr3_50" "Trial03_KRLr3_51" "Trial03_KRLr3_53" "Trial03_KRLr3_54"
## [41] "Trial03_KRLr3_55" "Trial03_KRLr3_56" "Trial03_KRLr3_57" "Trial04_KRLr4_58"
## [45] "Trial04_KRLr4_62" "Trial04_KRLr4_67" "Trial04_KRLr4_70" "Trial04_KRLr4_75"
## [49] "Trial04_KRLr4_76"
GRP_dtotal <- dtotal %>% group_by(KrillID)
dtotal <- GRP_dtotal


info <- lmList(oxygen ~ delta_t|KrillID, dtotal,na.action=na.omit)
#view(dtotal[!dtotal$KrillID %in% names(info), ])
9.a Missing Slope Value
MissingINFOobservations <- (dtotal[!dtotal$KrillID %in% names(info), ])
dtotalVSmissinfo <- summary(comparedf(dtotal, MissingINFOobservations))

kable(MissingINFOobservations)
KrillID SensorName Date Time User SensorID delta_t Unit Value Unit.1 Mode Phase Unit.2 Amplitude Unit.3 Temp Unit.4 patm Unit.5 Salinity Unit.6 Error Cal0 Unit.7 T0 Unit.8 O2.2nd Unit.9 Cal2nd Unit.10 T2nd Unit.11 CalPressure Unit.12 f1 dPhi1 dkSv1 dPhi2 dkSv2 m Cal.Mode SignalLEDCurrent ReferenceLEDCurrent ReferenceAmplitude DeviceSerial FwVersion SensorType BatchID Calibration.Date Sensor.lot PreSens.calibrated.Sensor Battery.Voltage Unit.13 Sequence FileName MOATS Treatment LoadingLocation GlassVialNumber Species TelsonLength..mm. Size dateTime TrialID.x percentDOassumpt assumedSatDOmg percentDO obseveredSatDOmg actualDOmg CorTemp SalinityConstant oxygen sapply(cSlopes, I) TrialID.y
9.b Exploring 3 Missing Observations
write.csv(MissingINFOobservations, file = "2020.11.16_MissingINFOobservations.csv", row.names = FALSE)

#Summary function commented out due to errors below

summary(comparedf(dtotal, MissingINFOobservations, by = "delta_t"))
## 
## 
## Table: Summary of data.frames
## 
## version   arg                        ncol   nrow
## --------  ------------------------  -----  -----
## x         dtotal                       74   2382
## y         MissingINFOobservations      74      0
## 
## 
## 
## Table: Summary of overall comparison
## 
## statistic                                                      value
## ------------------------------------------------------------  ------
## Number of by-variables                                             1
## Number of non-by variables in common                              73
## Number of variables compared                                      73
## Number of variables in x but not y                                 0
## Number of variables in y but not x                                 0
## Number of variables compared with some values unequal              0
## Number of variables compared with all values equal                73
## Number of observations in common                                   0
## Number of observations in x but not y                           2382
## Number of observations in y but not x                              0
## Number of observations with some compared variables unequal        0
## Number of observations with all compared variables equal           0
## Number of values unequal                                           0
## 
## 
## 
## Table: Variables not shared
## 
## |                        |
## |:-----------------------|
## |No variables not shared |
## 
## 
## 
## Table: Other variables not compared
## 
## |                                |
## |:-------------------------------|
## |No other variables not compared |
## 
## 
## 
## Table: Observations not shared
## 
## version    delta_t   observation
## --------  --------  ------------
## x             0.00             1
## x             0.00           837
## x             0.00          1297
## x             0.00          2125
## x             0.02             2
## x             0.02           838
## x             0.02          1298
## x             0.02          2126
## x             0.03             3
## x             0.03           839
## x             0.03          1299
## x             0.03          2127
## x             0.05           840
## x             0.05          1300
## x             0.05          2128
## x             0.17          1385
## x             0.18          1355
## x             0.20          1351
## x             0.22          1348
## x             0.33          1425
## x             0.35          1400
## x             0.37          1420
## x             0.38          1421
## x             0.52          1481
## x             0.53          1461
## x             0.55           896
## x             0.55          1466
## x             0.57           897
## x             0.57          1462
## x             0.58           907
## x             0.60           908
## x             0.62           921
## x             0.63           922
## x             0.63          2196
## x             0.65          2184
## x             0.67          2181
## x             0.68          2182
## x             0.83          1512
## x             0.85          1517
## x             0.87             4
## x             0.87          1491
## x             0.88             5
## x             0.88          1483
## x             0.90             6
## x             0.90          1494
## x             0.92             7
## x             1.02          1581
## x             1.03          1580
## x             1.05          1550
## x             1.07          1551
## x             1.08          1548
## x             1.20          1630
## x             1.22            74
## x             1.22          1627
## x             1.23            75
## x             1.23          1619
## x             1.25            62
## x             1.25          1588
## x             1.27            63
## x             1.27          1589
## x             1.40          1651
## x             1.42          1652
## x             1.43          1669
## x             1.45          1633
## x             1.47           104
## x             1.47          1638
## x             1.48           105
## x             1.50           119
## x             1.55          2232
## x             1.57          2233
## x             1.58          1729
## x             1.58          2234
## x             1.60          1732
## x             1.62          1731
## x             1.63          1698
## x             1.68           145
## x             1.70           147
## x             1.72           143
## x             1.75          1769
## x             1.77          1774
## x             1.78          1775
## x             1.80           937
## x             1.80          1776
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## x            87.18           711
## x            87.18          2089
## x            87.20           712
## x            87.20          2098
## x            87.22           713
## x            87.22          2099
## x            87.23           714
## x            87.23          2100
## x            87.25           702
## x            87.25          2093
## x            87.37           790
## x            87.38           799
## x            87.40           783
## x            87.42           787
## x            87.43           801
## x            87.45           785
## x            91.17           849
## x            91.18           850
## x            91.20           851
## x            91.70           891
## x            91.72           889
## x            91.73           890
## x            92.17           944
## x            92.18           945
## x            92.20           946
## x            92.32          1015
## x            92.33          1027
## x            92.35          1045
## x            92.37          1032
## x            92.38          1037
## x            92.82          1071
## x            92.83          1072
## x            92.85          1064
## x            92.87          1055
## x            93.32          1130
## x            93.33          1118
## x            93.35          1119
## x            93.37          1102
## x            93.62          1176
## x            93.63          1164
## x            93.65          1192
## x            93.67          1181
## x            93.80          1217
## x            93.82          1218
## x            93.83          1229
## x            94.00          1291
## x            94.02          1265
## x            94.03          1266
## x            94.05          1294
## x            97.12          2135
## x            97.13          2136
## x            97.15          2137
## x            97.67          2201
## x            97.68          2197
## x            97.70          2207
## x            97.72          2204
## x            97.73          2199
## x            97.75          2191
## x            97.77          2178
## x            97.78          2170
## x            98.72          1321
## x            98.73          1322
## x            98.75          1327
## x            98.77          1323
## x            98.78          1301
## x            98.90          1382
## x            98.90          2249
## x            98.92          1367
## x            98.92          2250
## x            98.93          1360
## x            98.95          1345
## x            99.10          1402
## x            99.12          1403
## x            99.12          2243
## x            99.13          1393
## x            99.13          2219
## x            99.15          1432
## x            99.15          2220
## x            99.17          1435
## x            99.17          2254
## x            99.28          1477
## x            99.30          1473
## x            99.32          1478
## x            99.33          1467
## x            99.57            40
## x            99.58            47
## x            99.60            44
## x            99.62            28
## x            99.63            33
## x            99.63          1501
## x            99.65          1497
## x            99.67          1526
## x            99.67          2269
## x            99.68          1530
## x            99.68          2261
## x            99.70          2258
## x            99.72          2263
## x            99.82          1565
## x            99.83          1570
## x            99.85          1571
## x            99.87          1568
## x            99.88          1569
## x            99.93            87
## x            99.95            84
## x            99.97            76
## x            99.98            61
## x           100.03          1629
## x           100.05          1610
## x           100.07          1604
## x           100.08           117
## x           100.08          1612
## x           100.10           118
## x           100.10          1617
## x           100.12           128
## x           100.13            95
## x           100.15            96
## x           100.22          1646
## x           100.23          1639
## x           100.25           161
## x           100.25          1632
## x           100.27           153
## x           100.27          1649
## x           100.28           144
## x           100.28          1650
## x           100.30           138
## x           100.32           140
## x           100.33           149
## x           100.42          1728
## x           100.43          1713
## x           100.45           191
## x           100.45          1718
## x           100.47           202
## x           100.47          1719
## x           100.48           196
## x           100.48          1716
## x           100.50           193
## x           100.52           194
## x           100.62          1762
## x           100.63          1754
## x           100.65          1751
## x           100.67          1752
## x           100.68          1757
## x           100.70           213
## x           100.70          2337
## x           100.72           211
## x           100.72          2334
## x           100.73           214
## x           100.73          2326
## x           100.75           205
## x           100.77           206
## x           100.78           203
## x           100.80           208
## x           100.82           212
## x           100.83          1783
## x           100.85          1819
## x           100.85          2344
## x           100.87          1824
## x           100.87          2354
## x           100.88          1822
## x           100.88          2357
## x           100.90          1818
## x           100.90          2358
## x           100.97           275
## x           100.98           272
## x           101.00           264
## x           101.02           265
## x           101.03           279
## x           101.03          1860
## x           101.05          1857
## x           101.07          1854
## x           101.08          1863
## x           101.10          1859
## x           101.15           335
## x           101.17           337
## x           101.18           325
## x           101.20           326
## x           101.22           336
## x           101.50          1907
## x           101.52          1919
## x           101.53           375
## x           101.53          1920
## x           101.55           377
## x           101.55          1921
## x           101.57           378
## x           101.57          1917
## x           101.58           384
## x           101.60           361
## x           101.70          1965
## x           101.72           418
## x           101.72          1956
## x           101.73           406
## x           101.73          1957
## x           101.75           407
## x           101.75          1962
## x           101.77           408
## x           101.77          1954
## x           101.78           386
## x           101.88          1990
## x           101.90           440
## x           101.90          1978
## x           101.92           445
## x           101.92          2000
## x           101.93           442
## x           101.93          1991
## x           101.95           438
## x           101.95          2002
## x           101.97           444
## x           101.98           439
## x           102.07          2062
## x           102.08          2056
## x           102.10          2061
## x           102.12           498
## x           102.12          2046
## x           102.13           512
## x           102.13          2043
## x           102.15           523
## x           102.17           500
## x           102.18           501
## x           102.20           489
## x           102.27          2118
## x           102.28          2097
## x           102.30          2086
## x           102.32           548
## x           102.32          2083
## x           102.33           536
## x           102.33          2088
## x           102.35           566
## x           102.37           558
## x           102.38           559
## x           102.52           603
## x           102.53           623
## x           102.55           620
## x           102.57           628
## x           102.58           626
## x           102.70           662
## x           102.72           668
## x           102.73           660
## x           102.75           676
## x           102.77           655
## x           102.88           722
## x           102.90           736
## x           102.92           734
## x           102.93           735
## x           102.95           739
## x           102.97           737
## x           103.10           782
## x           103.12           777
## x           103.13           780
## x           103.15           775
## x           103.17           762
## x           103.28           811
## x           103.30           812
## x           103.32           813
## x           103.33           814
## x           103.35           815
## x           103.37           816
## x           106.13           841
## x           106.15           842
## x           106.17           843
## x           106.18           844
## x           106.20           845
## x           106.73           886
## x           106.75           883
## x           106.77           882
## x           106.78           884
## x           106.80           888
## x           107.35           990
## x           107.37           991
## x           107.38           988
## x           107.40           965
## x           107.42           964
## x           107.70          1007
## x           107.72          1012
## x           107.73          1013
## x           107.75          1042
## x           107.77          1034
## x           107.78          1011
## x           108.23          1091
## x           108.25          1079
## x           108.27          1099
## x           108.28          1094
## x           108.30          1092
## x           108.93          1128
## x           108.95          1139
## x           108.97          1131
## x           108.98          1132
## x           109.00          1110
## x           109.15          1149
## x           109.17          1175
## x           109.18          1187
## x           109.20          1178
## x           109.22          1179
## x           109.37          1224
## x           109.38          1225
## x           109.40          1208
## x           109.42          1209
## x           109.43          1210
## x           109.60          1250
## x           109.62          1281
## x           109.63          1292
## x           109.65          1284
## x           109.67          1271
## x           112.53          2143
## x           112.55          2144
## x           112.57          2145
## x           113.10          2165
## x           113.12          2171
## x           113.13          2172
## x           113.15          2168
## x           113.70          1307
## x           113.72          1304
## x           113.73          1305
## x           113.75          1306
## x           113.77          1311
## x           113.88          1381
## x           113.88          2239
## x           113.90          1363
## x           113.90          2252
## x           113.92          1374
## x           113.92          2227
## x           113.93          1359
## x           113.93          2228
## x           113.95          1353
## x           114.07          1404
## x           114.07          1414
## x           114.08          1395
## x           114.10          1392
## x           114.12            27
## x           114.12          1394
## x           114.13            16
## x           114.15            17
## x           114.17            18
## x           114.23          1436
## x           114.25          1451
## x           114.27          1470
## x           114.28          1452
## x           114.30          1448
## x           114.35          2275
## x           114.37          2289
## x           114.38          2286
## x           114.40          2290
## x           114.43            69
## x           114.45            48
## x           114.47            49
## x           114.48            51
## x           114.60           123
## x           114.60          1505
## x           114.62           115
## x           114.62          1500
## x           114.63           135
## x           114.63          1487
## x           114.65           121
## x           114.65          1485
## x           114.67          1488
## x           114.77           180
## x           114.78           167
## x           114.78          1547
## x           114.80           142
## x           114.80          1558
## x           114.82           152
## x           114.82          1552
## x           114.83          1537
## x           114.85          1538
## x           114.92           231
## x           114.93           219
## x           114.95           220
## x           114.97           225
## x           114.98           232
## x           115.00          1615
## x           115.02          1613
## x           115.03          1597
## x           115.05          1590
## x           115.07          1587
## x           115.10          2298
## x           115.12           277
## x           115.12           284
## x           115.12          2300
## x           115.13           285
## x           115.13          2308
## x           115.15           287
## x           115.15          2305
## x           115.17           286
## x           115.22          1640
## x           115.23          1643
## x           115.25          1658
## x           115.25          2361
## x           115.27           329
## x           115.27          1659
## x           115.27          2362
## x           115.28           321
## x           115.28          1660
## x           115.28          2376
## x           115.30           331
## x           115.32           332
## x           115.33           310
## x           115.40          1717
## x           115.42          1712
## x           115.43          1703
## x           115.45          1684
## x           115.47          1689
## x           115.58          1763
## x           115.60          1759
## x           115.62          1740
## x           115.63          1734
## x           115.65          1738
## x           115.72           338
## x           115.73           349
## x           115.75           359
## x           115.77           346
## x           115.78           353
## x           115.78          1796
## x           115.80          1797
## x           115.82          1814
## x           115.83          1795
## x           115.85          1800
## x           115.90           402
## x           115.92           403
## x           115.93           419
## x           115.95           420
## x           115.97           394
## x           115.98          1861
## x           116.00          1862
## x           116.02          1851
## x           116.03          1836
## x           116.05          1830
## x           116.12           452
## x           116.12           456
## x           116.13           467
## x           116.15           468
## x           116.17           459
## x           116.30           497
## x           116.32           511
## x           116.33           525
## x           116.35           517
## x           116.37           527
## x           116.47          1890
## x           116.48          1881
## x           116.50           545
## x           116.50          1894
## x           116.52           546
## x           116.52          1887
## x           116.53           573
## x           116.53          1888
## x           116.55           572
## x           116.57           563
## x           116.67          1960
## x           116.68           611
## x           116.68          1942
## x           116.70           608
## x           116.70          1931
## x           116.72           618
## x           116.72          1928
## x           116.73           624
## x           116.73          1933
## x           116.75           610
## x           116.87           659
## x           116.87          1981
## x           116.88           669
## x           116.88          1975
## x           116.90           661
## x           116.90          2001
## x           116.92           649
## x           116.92          2003
## x           116.93           640
## x           116.93          2008
## x           117.05           703
## x           117.07           704
## x           117.08           692
## x           117.08          2055
## x           117.10           706
## x           117.10          2040
## x           117.12           683
## x           117.12          2027
## x           117.13          2032
## x           117.15          2037
## x           117.23           746
## x           117.25           744
## x           117.27           763
## x           117.28           776
## x           117.30           772
## x           117.30          2104
## x           117.32          2077
## x           117.33          2076
## x           117.35          2071
## x           117.37          2078
## x           117.42           798
## x           117.43           795
## x           117.45           796
## x           117.47           797
## x           117.48           789
## x           117.50           784
## x           120.33           848
## x           120.35           861
## x           120.37           862
## x           120.38           863
## x           120.40           864
## x           121.07           914
## x           121.08           915
## x           121.10           916
## x           121.12           925
## x           121.13           919
## x           122.00           985
## x           122.02           986
## x           122.03           987
## x           122.05           951
## x           122.07           952
## x           122.22          1031
## x           122.47          1033
## x           122.48          1035
## x           122.50          1024
## x           122.52          1028
## x           122.53          1005
## x           122.98          1081
## x           123.00          1090
## x           123.02          1082
## x           123.03          1068
## x           123.05          1060
## x           124.35          1115
## x           124.37          1121
## x           124.38          1122
## x           124.40          1109
## x           124.42          1123
## x           124.58          1169
## x           124.60          1166
## x           124.62          1180
## x           124.63          1158
## x           124.65          1155
## x           124.83          1223
## x           124.85          1221
## x           124.87          1199
## x           124.88          1195
## x           125.00          1267
## x           125.02          1268
## x           125.03          1286
## x           125.05          1287
## x           125.07          1288
## x           128.72          1334
## x           128.73          1335
## x           128.75          1343
## x           128.77          1333
## x           128.83          2134
## x           128.85          2162
## x           128.87          1379
## x           128.87          2159
## x           128.88          1386
## x           128.90          1383
## x           128.92          1384
## x           129.03          1419
## x           129.05          1424
## x           129.07          1416
## x           129.08          1417
## x           129.17            39
## x           129.18            45
## x           129.20            37
## x           129.22            43
## x           129.22          1439
## x           129.23          1437
## x           129.25          1458
## x           129.27          1463
## x           129.28          1472
## x           129.47          2206
## x           129.48          2202
## x           129.50            82
## x           129.50          2200
## x           129.52            70
## x           129.53            57
## x           129.55            58
## x           129.58          1513
## x           129.60          1510
## x           129.62          1511
## x           129.63          1503
## x           129.65            99
## x           129.65          1508
## x           129.67           133
## x           129.68           130
## x           129.70           134
## x           129.77          1531
## x           129.78          1574
## x           129.80          1575
## x           129.82          1576
## x           129.83           170
## x           129.83          1579
## x           129.85           172
## x           129.87           173
## x           129.88           183
## x           129.95          1623
## x           129.97          1624
## x           129.98          1620
## x           130.00           217
## x           130.00          1625
## x           130.02           227
## x           130.02          1626
## x           130.03           228
## x           130.05           234
## x           130.13          1648
## x           130.15           256
## x           130.15          1645
## x           130.17           244
## x           130.17          1641
## x           130.18           249
## x           130.18          1642
## x           130.18          2226
## x           130.20           246
## x           130.20          1647
## x           130.20          2214
## x           130.22           260
## x           130.22          1644
## x           130.22          2215
## x           130.23          2216
## x           130.32           288
## x           130.33           296
## x           130.33          1726
## x           130.35           317
## x           130.35          1727
## x           130.37           291
## x           130.37          1724
## x           130.38           304
## x           130.38          1725
## x           130.40          1730
## x           130.55          1772
## x           130.57          1768
## x           130.58          1765
## x           130.60          1770
## x           130.62          1767
## x           130.62          2293
## x           130.63          2277
## x           130.65          2278
## x           130.70           355
## x           130.72           340
## x           130.73           345
## x           130.73          1784
## x           130.75           339
## x           130.75          1782
## x           130.77           344
## x           130.77          1802
## x           130.78          1788
## x           130.80          1827
## x           130.90           415
## x           130.92           423
## x           130.92          1866
## x           130.93           431
## x           130.93          1871
## x           130.95           432
## x           130.95          1872
## x           130.97           433
## x           130.97          1873
## x           130.98          1865
## x           131.08           462
## x           131.10           463
## x           131.12           464
## x           131.13           450
## x           131.15           455
## x           131.27           520
## x           131.28           521
## x           131.30           522
## x           131.32           482
## x           131.33           495
## x           131.38          1924
## x           131.40          1925
## x           131.42          1926
## x           131.43           551
## x           131.43          1923
## x           131.45           565
## x           131.45          1909
## x           131.47           567
## x           131.48           533
## x           131.48          2341
## x           131.50           539
## x           131.50          2323
## x           131.52          2310
## x           131.53          2324
## x           131.57          1972
## x           131.58          1967
## x           131.60          1971
## x           131.62          1964
## x           131.62          2380
## x           131.63           607
## x           131.63          1946
## x           131.63          2381
## x           131.65           604
## x           131.65          2382
## x           131.67           591
## x           131.68           585
## x           131.70           586
## x           131.75          1987
## x           131.77          1992
## x           131.78          2021
## x           131.80          2019
## x           131.82           637
## x           131.82          2007
## x           131.83           643
## x           131.85           653
## x           131.87           634
## x           131.88           644
## x           131.95          2070
## x           131.97          2067
## x           131.98          2068
## x           132.00          2064
## x           132.02           687
## x           132.02          2031
## x           132.03           684
## x           132.05           699
## x           132.07           700
## x           132.08           691
## x           132.15          2119
## x           132.17          2120
## x           132.18          2121
## x           132.20           748
## x           132.20          2122
## x           132.22           741
## x           132.22          2123
## x           132.23           774
## x           132.23          2124
## x           132.25           751
## x           132.27           740
## x           132.38           831
## x           132.40           832
## x           132.42           833
## x           132.43           834
## x           132.45           835
## x           132.47           836
## x           137.02           852
## x           137.03           853
## x           137.05           854
## x           137.65           887
## x           137.67           895
## x           137.68           930
## x           137.70           929
## x           138.15           943
## x           138.17           935
## x           138.18           936
## x           138.20           933
## x           138.22           934
## x           138.30          1039
## x           138.32          1029
## x           138.35          1020
## x           138.37          1048
## x           138.38          1021
## x           138.40          1025
## x           138.87          1056
## x           138.88          1074
## x           138.90          1075
## x           138.92          1076
## x           138.93          1086
## x           139.65          1191
## x           139.67          1193
## x           139.68          1161
## x           139.70          1167
## x           140.20          1230
## x           140.22          1231
## x           140.23          1228
## x           140.25          1211
## x           140.43          1278
## x           140.45          1279
## x           140.47          1280
## x           140.48          1296
## 
## 
## 
## Table: Differences detected by variable
## 
## var.x                       var.y                         n   NAs
## --------------------------  --------------------------  ---  ----
## KrillID                     KrillID                       0     0
## SensorName                  SensorName                    0     0
## Date                        Date                          0     0
## Time                        Time                          0     0
## User                        User                          0     0
## SensorID                    SensorID                      0     0
## Unit                        Unit                          0     0
## Value                       Value                         0     0
## Unit.1                      Unit.1                        0     0
## Mode                        Mode                          0     0
## Phase                       Phase                         0     0
## Unit.2                      Unit.2                        0     0
## Amplitude                   Amplitude                     0     0
## Unit.3                      Unit.3                        0     0
## Temp                        Temp                          0     0
## Unit.4                      Unit.4                        0     0
## patm                        patm                          0     0
## Unit.5                      Unit.5                        0     0
## Salinity                    Salinity                      0     0
## Unit.6                      Unit.6                        0     0
## Error                       Error                         0     0
## Cal0                        Cal0                          0     0
## Unit.7                      Unit.7                        0     0
## T0                          T0                            0     0
## Unit.8                      Unit.8                        0     0
## O2.2nd                      O2.2nd                        0     0
## Unit.9                      Unit.9                        0     0
## Cal2nd                      Cal2nd                        0     0
## Unit.10                     Unit.10                       0     0
## T2nd                        T2nd                          0     0
## Unit.11                     Unit.11                       0     0
## CalPressure                 CalPressure                   0     0
## Unit.12                     Unit.12                       0     0
## f1                          f1                            0     0
## dPhi1                       dPhi1                         0     0
## dkSv1                       dkSv1                         0     0
## dPhi2                       dPhi2                         0     0
## dkSv2                       dkSv2                         0     0
## m                           m                             0     0
## Cal.Mode                    Cal.Mode                      0     0
## SignalLEDCurrent            SignalLEDCurrent              0     0
## ReferenceLEDCurrent         ReferenceLEDCurrent           0     0
## ReferenceAmplitude          ReferenceAmplitude            0     0
## DeviceSerial                DeviceSerial                  0     0
## FwVersion                   FwVersion                     0     0
## SensorType                  SensorType                    0     0
## BatchID                     BatchID                       0     0
## Calibration.Date            Calibration.Date              0     0
## Sensor.lot                  Sensor.lot                    0     0
## PreSens.calibrated.Sensor   PreSens.calibrated.Sensor     0     0
## Battery.Voltage             Battery.Voltage               0     0
## Unit.13                     Unit.13                       0     0
## Sequence                    Sequence                      0     0
## FileName                    FileName                      0     0
## MOATS                       MOATS                         0     0
## Treatment                   Treatment                     0     0
## LoadingLocation             LoadingLocation               0     0
## GlassVialNumber             GlassVialNumber               0     0
## Species                     Species                       0     0
## TelsonLength..mm.           TelsonLength..mm.             0     0
## Size                        Size                          0     0
## dateTime                    dateTime                      0     0
## TrialID.x                   TrialID.x                     0     0
## percentDOassumpt            percentDOassumpt              0     0
## assumedSatDOmg              assumedSatDOmg                0     0
## percentDO                   percentDO                     0     0
## obseveredSatDOmg            obseveredSatDOmg              0     0
## actualDOmg                  actualDOmg                    0     0
## CorTemp                     CorTemp                       0     0
## SalinityConstant            SalinityConstant              0     0
## oxygen                      oxygen                        0     0
## sapply(cSlopes, I)          sapply(cSlopes, I)            0     0
## TrialID.y                   TrialID.y                     0     0
## 
## 
## 
## Table: Differences detected
## 
## |                        |
## |:-----------------------|
## |No differences detected |
## 
## 
## 
## Table: Non-identical attributes
## 
## |                            |
## |:---------------------------|
## |No non-identical attributes |
#Resulting Faults
#...Non-identical attributes
#...No non-identical attributes


# summary.comparedf(dtotal, MissingINFOobservations, by = delta_t)

#kable(Incld_UniqueKrillIDs)

9.C Comparison between Krillr4_58 and 59 to better determine differences

Using neighboring observations to determine if any difference

dRESP_58 <- read.csv(file = "2020.11.16_REPRwork_KRLr4_58comparison.csv", stringsAsFactors = FALSE)
dRESP_59 <- read.csv(file = "2020.11.16_REPRwork_KRLr4_59comparison.csv", stringsAsFactors = FALSE)

comparedf(dRESP_58, dRESP_59)
## Compare Object
## 
## Function Call: 
## comparedf(x = dRESP_58, y = dRESP_59)
## 
## Shared: 52 non-by variables and 41 observations.
## Not shared: 0 variables and 9 observations.
## 
## Differences found in 10/52 variables compared.
## 0 variables compared have non-identical attributes.
# Compare Object
# 
# Function Call: 
# comparedf(x = dRESP_58, y = dRESP_59)
# 
# Shared: 52 non-by variables and 41 observations.
# Not shared: 0 variables and 9 observations.
# 
# Differences found in 10/52 variables compared.
# 0 variables compared have non-identical attributes.


comparedf(dRESP_58, dRESP_59, by = "delta_t")
## Compare Object
## 
## Function Call: 
## comparedf(x = dRESP_58, y = dRESP_59, by = "delta_t")
## 
## Shared: 51 non-by variables and 0 observations.
## Not shared: 0 variables and 91 observations.
## 
## Differences found in 0/51 variables compared.
## 0 variables compared have non-identical attributes.

9.d Comparing the slopes of 58 and 59

GRP_dtotal 
write.csv(GRP_dtotal, file = "2020.11.16_GRP_dtotalObservations.csv", row.names = FALSE)


GRP_dtotal_58 <- read.csv(file = "2020.11.16_GRP_dtotalObservationsKRL4_58.csv", stringsAsFactors = FALSE)
dtotal_58_filter <- filter(dtotal, KrillID == "Trial04_KRLr4_58")


GRP_dtotal_59 <- read.csv(file = "2020.11.16_GRP_dtotalObservationsKRL4_59.csv", stringsAsFactors = FALSE)
dtotal_59_filter <- filter(dtotal, KrillID == "Trial04_KRLr4_59")



GRP_dtotal_68 <- read.csv(file = "2020.11.16_GRP_dtotalObservationsKRL4_68.csv", stringsAsFactors = FALSE)
GRP_dtotal_69 <- read.csv(file = "2020.11.16_GRP_dtotalObservationsKRL4_69.csv", stringsAsFactors = FALSE)

# Krill58plot <-    ggplot(GRP_dtotal_58, 
#                 aes(x=Time, 
#                 y=oxygen))
# 
# Krill58plot


Krill58plot2 <- ggplot(GRP_dtotal_58, aes(delta_t, oxygen)) +
                geom_boxplot(notch = TRUE, outlier.shape = NA, colour = "green") +
                geom_point(data = GRP_dtotal_58, aes(x=delta_t, y=oxygen), size=5, color = "purple") + 
                ggtitle("Boxplot for Krill 58 observations") +
            theme_bw() 

Krill58plot2
## Warning: Continuous x aesthetic -- did you forget aes(group=...)?

# comparedf(dRESP_58, dRESP_59, by = "oxygen")

9.x T/S the linear model list function

# levels(dtotal$KrillID)
# 
# ##### Krill 58
# lm58 <- lm(oxygen ~ delta_t, GRP_dtotal_58, na.action=na.omit)
# info58 <- lmList(oxygen ~ delta_t|KrillID, GRP_dtotal_58, na.action=na.omit)
# GRP_dtotal_58$KrillID <- factor(GRP_dtotal_58$KrillID)
# levels(GRP_dtotal_58$KrillID)
# 
# 
# lm58f <- lm(oxygen ~ delta_t, dtotal_58_filter, na.action=na.omit)
# info58f <- lmList(oxygen ~ delta_t|KrillID, dtotal_58_filter, na.action=na.omit)
# 
# 
# info58 <- lmList(oxygen ~ delta_t|KrillID, GRP_dtotal_58, na.action=na.omit)
# GRP_dtotal_58$KrillID <- factor(GRP_dtotal_58$KrillID)
# levels(GRP_dtotal_58$KrillID)
# 
# 
# ### Krill 59
# 
# #using the filtered dtotal database rather than kate's copy and paste file
# lm59f <- lm(oxygen ~ delta_t, dtotal_59_filter, na.action=na.omit)
# info59f <- lmList(oxygen ~ delta_t|KrillID, dtotal_59_filter, na.action=na.omit)
# levels(dtotal_59_filter$KrillID)
# 
# 
# # working off of kate's copy paste file
# lm59 <- lm(oxygen ~ delta_t, GRP_dtotal_59, na.action=na.omit)
# info59 <- lmList(oxygen ~ delta_t|KrillID, GRP_dtotal_59, na.action=na.omit)
# 
# 
# #GRP_dtotal_59 <- subset(GRP_dtotal_59, KrillID != "")
# GRP_dtotal_59a <- filter(GRP_dtotal_59, KrillID = "")
# 
# 
# GRP_dtotal_59$KrillID <- factor(GRP_dtotal_59$KrillID)
# levels(GRP_dtotal_59$KrillID)
# 
# 
# 
# ### hunting for missing values
# dtotal59fmissingOXY <- filter(dtotal_59_filter, is.na(oxygen))
# dotal59fmissingDELT <- filter(dtotal_59_filter, is.na(delta_t))
# # no missing values found 

write.csv(dtotal, file = "2020.11.16_dtotal_TSlinearmodel.csv", row.names = FALSE)

9.e Creating a small box plot for Krill 59

Krill59plot <- ggplot(GRP_dtotal_59, aes(delta_t, oxygen)) +
                geom_boxplot(notch = TRUE, outlier.shape = NA, colour = "green") +
                geom_point(data = GRP_dtotal_59, aes(x=delta_t, y=oxygen), size=5, color = "purple") + 
                ggtitle("Boxplot for Krill 59 observations") +
            theme_bw() 

Krill59plot
## Warning: Continuous x aesthetic -- did you forget aes(group=...)?
## Warning: Removed 727 rows containing missing values (stat_boxplot).
## Warning: Removed 727 rows containing missing values (geom_point).

9.f Creating a small box plot for Krill 68

Krill68plot <- ggplot(GRP_dtotal_68, aes(delta_t, oxygen)) +
                geom_boxplot(notch = TRUE, outlier.shape = NA, colour = "green") +
                geom_point(data = GRP_dtotal_68, aes(x=delta_t, y=oxygen), size=5, color = "purple") + 
                ggtitle("Boxplot for Krill 58 observations") +
            theme_bw() 

Krill68plot
## Warning: Continuous x aesthetic -- did you forget aes(group=...)?

9.g Creating a small box plot for Krill 69

Krill69plot <- ggplot(GRP_dtotal_69, aes(delta_t, oxygen)) +
                geom_boxplot(notch = TRUE, outlier.shape = NA, colour = "green") +
                geom_point(data = GRP_dtotal_69, aes(x=delta_t, y=oxygen), size=5, color = "purple") + 
                ggtitle("Boxplot for Krill 58 observations") +
            theme_bw() 

Krill69plot
## Warning: Continuous x aesthetic -- did you forget aes(group=...)?

#10.) Creating the linear Model on the Slope (Sapply)

info <- lmList(oxygen ~ delta_t|KrillID, dtotal,na.action=na.omit)

##10.a) Trouble Shooting the Linear Model Problems

# summary(lm(oxygen ~ delta_t, data= dtotal[dtotal$KrillID=="Trial04_KRLr4_59",]))$r.squared
# 
# lm(oxygen ~ delta_t, data= dtotal[dtotal$KrillID=="Trial04_KRLr4_68",])
# 
# lm(oxygen ~ delta_t, data= dtotal[dtotal$KrillID=="Trial04_KRLr4_69",])
# 
# 
# dtotal[is.na(dtotal$delta_t),]
# unique(dtotal$KrillID)
# 
# names(info)
# 
# view(dtotal[!dtotal$KrillID %in% names(info), ])
# 
# 
# print(info)
# 
# # slopes <- coef(info)[2]
# # #print(slopes)
# # dslopes <- data.matrix(slopes)
# # #View(dref)
# # mode(dslopes[,1])
# # dslopes <- as.data.frame(dslopes)
# # dslopes$slope <- dslopes$delta_t
# # dslopes$delta_t <- NULL
# # #View(dslopes)
# 
# #now for R^2!!
# Rsq <- sapply(info,function(x) summary(x)$r.squared)
# t(Rsq) #transposes rows and columns
# Rsq <- data.matrix(Rsq)
# #View(Rsq)
# dtotal <- cbind(ds, Rsq)
# View(dtotal)
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